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AI path Β· course 19 of 54
Vision Transformers
Advanced Β· 5 lessons Β· 0 complete
Learn how the transformer architecture, originally designed for text, was adapted to process images through the Vision Transformer (ViT), and how self-attention creates a genuine alternative to the convolutional approach that has dominated computer vision for over a decade. This is part 3 of the Computer Vision Deep Dive track, building on object detection and image segmentation, and it's for learners who already understand CNNs and want to know how transformers changed the field. By the end you'll be able to reason clearly about when a ViT is the right tool and when a CNN still wins.
